Technical Onboarding

Bookmark this page for quick access to team resources

Analysts

• See below for list of our collaboration and analysis tools.

• As part of your onboarding, privileges have already been created for you to access the resources below.

Non-Analyst Team Members

• Any of the tools below are available to you as well!

If you still need help with access, use the information at the bottom of this page to get help.

Collaboration Tools:

• Slack | (Docs)

• Analytics Repo | (Docs)

• Analyst Project Board | (Docs)

• Google Cloud Storage | (Docs)

Analytics Tools:

• notebooks.calitp.org - JupyterHub cloud-based notebooks for querying Python, SQL, R | (Docs)

• dashboards.calitp.org - Metabase business insights & dashboards | (Docs)

• dbt-docs.calitp.org - Documentation for the Cal-ITP data warehouse.

• analysis.calitp.org - The Cal-ITP analytics portfolio website.

• Google BigQuery - Viewing the data warehouse and querying SQL

Python Libraries:

• calitp-data-analysis - Cal-ITP’s internal Python library for analysis | (Docs)

• siuba - Recommended data analysis library | (Docs)

• shared_utils and here - A shared utilities library for the analytics team | (Docs)

Caltrans Employee Resources:

• OnRamp - Caltrans employee intranet

• Service Now (SNOW) - Caltrans IT Service Management Portal for IT issues and requesting specific software

• Cal Employee Connect - State Controller’s Office site for paystubs and tax information

• Geospatial Enterprise Engagement Platform - GIS Account Request Form (optional) - User request form for ArcGIS Online and ArcGIS Portal accounts

 

Still need access to a non-Caltrans tool above?

Ask on the #services-team channel in the Cal-ITP Slack.

New Analyst Training Curriculum

This is a rough guide to your first few weeks on our team:

1. Week 1 – Introduction to Caltrans, Cal-ITP, and Division of Data & Digital Services: Includes non-technical 1:1 chats with the rest of the analyst team to meet and discuss ongoing and past projects. Also includes peer-guided introduction to transit data and transportation grants concepts.

2. Weeks 1-2 – Technical onboarding (GitHub, JupyterHub, Google products): Includes working through an example push/pull/commit workflow with your Personal README.

3. Weeks 2-3 – Introduction to our data: Includes learning what is in and how to access our data warehouse and Airtable, with Python and in Metabase. Also includes basic data visualization concepts.

4. Weeks 4-5 – Python training curriculum: Includes foundational concepts and team-specific starter kit exercises.

5. 6-Month mark – Option to explore intermediate Python concepts with more tutorials.